README.md

In SQIpro: Comprehensive Soil Quality Index Computation and Visualization

SQIpro

Comprehensive Soil Quality Index Computation and Visualization in R

Overview

SQIpro provides a complete, modular framework for computing the Soil Quality Index (SQI) — a single numeric score (0–1) integrating physical, chemical, and biological soil properties.

Six indexing methods

| Method | Reference | Key feature | |--------|-----------|-------------| | Linear Scoring | Doran & Parkin (1994) | Simple, equal-weight additive | | Regression-based | Masto et al. (2008) | Weights by regression coefficients | | PCA-based | Andrews et al. (2004) | Data-driven, variance-explained weights | | Fuzzy Logic | Zhu et al. (2010) | Handles uncertainty; geometric mean option | | Entropy Weighting | Shannon (1948) | Objective weights from information content | | TOPSIS | Hwang & Yoon (1981) | Multi-criteria ideal-solution distance |

Four scoring function types

"more"  — Higher is better   ▁▃▅▇█  (e.g., organic carbon)
"less"  — Lower is better    █▇▅▃▁  (e.g., bulk density)
"opt"   — Optimum range      ▁▅█▅▁  (e.g., pH 6.0–7.0)
"trap"  — Trapezoidal        ▁▅███▅▁ (explicit boundaries)

Installation

# Install from CRAN
install.packages("SQIpro")

Quick Start

library(SQIpro)

# 1. Load data
data(soil_data)

# 2. Define variable configuration
cfg <- make_config(
  variable = c("pH",  "EC",   "BD",   "OC",   "MBC",  "Clay"),
  type     = c("opt", "less", "less", "more", "more", "opt"),
  opt_low  = c(6.0,   NA,     NA,     NA,     NA,     20),
  opt_high = c(7.0,   NA,     NA,     NA,     NA,     35)
)

# 3. Score variables (0–1 transformation)
scored <- score_all(soil_data, cfg, group_cols = c("LandUse", "Depth"))

# 4. Select Minimum Data Set
mds <- select_mds(scored, group_cols = c("LandUse", "Depth"))

# 5. Compute and compare all methods
results <- sqi_compare(scored, cfg,
                        group_cols = c("LandUse", "Depth"),
                        dep_var    = "OC", mds = mds)
print(results)

Full Workflow

validate_data()  →  make_config()  →  plot_scoring_curves()
       ↓
   score_all()  →  select_mds()
       ↓
  sqi_linear()  sqi_pca()  sqi_regression()
  sqi_fuzzy()   sqi_entropy()  sqi_topsis()
       ↓
  sqi_compare()  →  sqi_anova()  →  sqi_sensitivity()
       ↓
  plot_sqi()  plot_scores()  plot_radar()  plot_sensitivity()

References

• Doran, J.W., & Parkin, T.B. (1994). Defining and assessing soil quality. In: Doran, J.W., Coleman, D.C., Bezdicek, D.F., & Stewart, B.A. (Eds.), Defining Soil Quality for a Sustainable Environment (pp. 3–21). SSSA Special Publication No. 35.

• Andrews, S.S., Karlen, D.L., & Cambardella, C.A. (2004). The soil management assessment framework: A quantitative soil quality evaluation method. Soil Science Society of America Journal, 68(6), 1945–1962.

• Bastida, F., Zsolnay, A., Hernández, T., & García, C. (2008). Past, present and future of soil quality indices: A biological perspective. Geoderma, 147(3), 159–171.

• Masto, R.E., Chhonkar, P.K., Purakayastha, T.J., Patra, A.K., & Singh, D. (2008). Soil quality indices for evaluation of long-term land use and soil management practices in semi-arid sub-tropical India. Land Degradation & Development, 19(5), 516–529.

• Hwang, C.L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag.

• Shannon, C.E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423.

Citation

citation("SQIpro")

License

GPL-3 © Sadikul Islam

SQIpro documentation built on April 20, 2026, 5:06 p.m.